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About

Doron Nussbaum is a researcher whose work lies at the intersection of algorithmic robotics, path planning, and multi-agent coordination. His most influential contribution addresses the fundamental problem of rendezvous: calculating the meeting point of scattered robots on weighted terrain surfaces (2005, 18 citations). This work provides a discretization approach for continuous surfaces, enabling efficient coordination in complex environments. Nussbaum has made significant advances in Moving Target Search (MTS), introducing subgoal graphs to enable real-time pursuit of moving entities—a problem critical to video games and dynamic robotics. His 2015 and 2021 papers on this topic (13 and 11 citations respectively) demonstrate sustained impact in this challenging domain. Beyond pursuit, Nussbaum has contributed to sensor fusion for mobile robotics, showing how vision-based maps can be improved by integrating sonar and infrared data (2004, 8 citations). His more recent work tackles the intriguing problem of catching a robot intruder with limited information (2020), where the pursuer must act on infrequent location snapshots. Across his career, Nussbaum has developed practical algorithms that balance theoretical rigor with real-time performance constraints, making his research valuable for both academic study and applied robotics.